Volltext-Downloads (blau) und Frontdoor-Views (grau)

Raman-Microspectroscopy for the Detection of Spoilage Bacteria

  • Raman-microspectroscopy was used for the non-destructive characterization and differentiation of six different meat spoilage associated microorganisms, namely Brochothrix thermosphacta DSM 20171, Micrococcus luteus, Pseudomonas fluorescens DSM 4358, Escherichia coli Top10 and K12 and Pseudomonas fluorescens DSM 50090. To evaluate and classify the Raman-spectroscopic data at species and strain level an adequate preprocessing and subsequent principal component analysis was used. The same procedure was extended to an independent test data set, which could be successfully assigned to the correct bacterial species and even to the right strain. The evaluation was not only successful in differentiation of gram-positive and gram-negative bacteria but also the discrimination between the different bacterial species and strains was possible. This means that the training data set, the preprocessing method and the evaluation of the data lead to a robust principal component analysis. Even the correct assignment of unknown samples is possible. The results show that Raman-microspectroscopy in combination with an appropriate chemometric treatment can be a good tool for a rapid examination and classification of microbial cultures.

Export metadata

Additional Services

Search Google Scholar Check availability


Show usage statistics
Document Type:Conference Object
Author:Daniel Klein, Claudia Wickleder, Peter Kaul
Parent Title (English):Holzhauer, Obergassel et al. (Hg.): Ressourcen-Wissen: Hebung ungenutzter Potenziale, Tagungsband Vortragsveranstaltung der Fachgruppe Ressourcen des Graduierteninstitutes NRW, 16. März 2017
First Page:74
Last Page:81
Publisher:Graduierteninstitut NRW
Publication year:2017
Funding:This work was funded by the German Research Foundation (DFG) as part of the research training group GRK 1564 'Imaging New Modalities'.
Departments, institutes and facilities:Fachbereich Angewandte Naturwissenschaften
Dewey Decimal Classification (DDC):6 Technik, Medizin, angewandte Wissenschaften / 66 Chemische Verfahrenstechnik / 660 Chemische Verfahrenstechnik
Entry in this database:2018/02/01